581 datasets found

Ember: an open dataset for training static pe malware machine learning models

Single-cell perturbation response prediction using machine learning.

The dataset used in the paper for real-time adaptive safety-critical control with Gaussian processes in high-order uncertain models.

Applications of machine learning in healthcare often require working with time-to-event prediction tasks including prognostication of an adverse event, re-hospitalization, and...

The dataset used in this paper for classification tasks on spherical-MNIST, atomic energy, Shrec17 data sets, and group testing on diffusion MRI data.

OGB-LSC provides the three large-scale realistic benchmark datasets, covering the core graph ML tasks of node classification, link prediction, and graph regression.

The dataset contains data from human-level control through deep reinforcement learning.

The VGG-16 and ResNet-50 DNNs are used as victim DNNs in the attack.

The VGG and ResNet DNNs are used as victim DNNs in the attack.

The dataset used in the paper is the PapersWithCode dataset, which contains papers and code from various machine learning conferences.

A collection of heterogeneous visual reasoning data sets and an interesting benchmark for two reasons: First, visual reasoning programs tend to be large (in current program...

The Cora and Citeseer datasets are used for training machine learning models to classify documents into different categories.

The dataset contains three challenging scenarios for flow prediction: incompressible and transonic flows, as well as isotropic turbulence.

The Titanic dataset contains information about passengers of the Titanic ship, including demographic and survival data.

The Bank Marketing dataset is a commonly used dataset in the fairness literature, containing information about individuals' demographic and economic characteristics.

The Adult Census dataset contains information about individuals from the 1994 U.S. census, including age, sex, and income.

The dataset used in this paper for convolutional neural networks (CNNs) with approximate multiplication.

The dataset used in this paper is the German dataset, which is a real-world UCI Machine Learning dataset extracted from a German bank for default prediction.

A commonly observed pattern in machine learning models is an underprediction of the target feature, with the model’s predicted target rate for members of a given category...

The dataset used in this work is a custom synthetic dataset generated using the liquid-dsp library, containing 600000 examples of each of 13.8 million examples, with SNRs...